An analysis of replenishment model of deteriorating items with ramp-type demand and trade credit under the learning effect
Archana Sharma,
Usha Sharma and
Chaman Singh
International Journal of Procurement Management, 2018, vol. 11, issue 3, 313-342
Abstract:
Effective management and control strategies are prerequisites in order to optimise inventory related decisions. Robust replenishment model can reduce overall inventory cost and increase financial surplus for the organisation. Adoption of trade credit strategy for deteriorating items provides economic benefits to the retailer (buyer) in settling the account for the fixed period and boosts the sales of the organisation. Therefore, in this proposed model trade credit is introduced and demands pattern follows ramp-type which is quadratic function of time for decaying items. Shortages are allowed and partially backlogged where the backlogging rate is dependent of waiting time. The inflation factor is also considered to propose realistic environment. Additionally, this study also considered the cost components which are followed by learning curve to improve the total inventory cost with strategic scheduling. Finally, the model is analysed through numerical examples and the sensitivity analysis is performed to test the robustness of the model.
Keywords: ramp-type demand; partial backlogging; learning effect; trade credit; inflation. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.inderscience.com/link.php?id=91668 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpman:v:11:y:2018:i:3:p:313-342
Access Statistics for this article
More articles in International Journal of Procurement Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().